This invention relates generally to the reduction of emission levels of one or more pollutants emitted from a fossil-fired combustion process and is particularly directed to a method for optimizing and controlling each of multiple inputs of injected substance (such as natural gas, ammonia, urea, oil, a water-oil emulsion, or a coal-water slurry) above the primary combustion zone of the process for reducing the emission levels of oxides of nitrogen (NOx), carbon monoxide (CO), and other pollutants, and for determining whether it is more cost effective to further reduce emissions with the injection of additional substance or to purchase emission credits on the open market.
The introduction of the Clean Air Act Amendments of 1990 delineated environmental. constraints requiring reduction of NOx emissions from electric utility and industrial boilers. Since 1990, many utilities have implemented expensive physical boiler modifications, such as the conversion to low-NOx coal burner technology, which achieved 25 to 50% NOx reductions. Throughout the Eastern United States more stringent regulations will require power plants to reduce NOx emissions by an average of 55 to 65% from 1990 levels by 2005. Additional physical/operational boiler modifications are being considered to achieve the remaining 5 to 40% reduction. These modifications may include a broader array of technologies, such as the injection of ammonia or urea into the upper region of the furnace and/or natural gas reburning.
Natural gas reburning has been shown to be an effective control technique to significantly reduce the NOx emissions of coal-fired boilers. In conventional gas reburning, 10 to 20% of the total heat input to the boiler is provided by natural gas injected into the upper region of the furnace above the primary combustion zone. This produces a slightly fuel-rich zone where NOx is chemically reduced to form atmospheric nitrogen. Overfire air is injected downstream of the reburn zone to provide sufficient air to complete the combustion process and minimize CO emissions. The amount of NOx reduction from reburning typically increases with the amount of natural gas injected.
Energy Systems Associates (ESA) of Pittsburgh, Pennsylvania and the Gas Research Institute (GRI) of Chicago, Illinois have developed and tested a new, more cost-effective, natural gas reburning process for NOx control called the Fuel Lean Gas Reburn (FLGR) technology. FLGR relies on the controlled injection of 3 to 7% natural gas heat input into the upper region of the furnace of coal-fired boilers to achieve a 35 to 45% NOx reduction. Similar to conventional gas reburning systems, FLGR employs natural gas injected above the furnace""s primary combustion zone to reduce much of the NOx to atmospheric nitrogen. However, with FLGR, the natural gas is injected in such a way that the furnace""s stoichiometry is optimized on a very localized basis, avoiding the formation of fuel-rich zones and maintaining overall fuel-lean conditions in the furnace. The natural gas is injected at low flue gas temperatures (2000xc2x0 F. to 2300xc2x0 F.) using multiple, high-velocity turbulent gas jets that penetrate into the upper furnace areas which have the highest NOx concentrations. Because the furnace is maintained overall fuel-lean, no downstream overfire completion air is needed to maintain acceptable levels of CO in the stack gas emission. These conceptual and operational differences of the FLGR system result in a more costeffective means of reducing NOx emissions over the conventional gas reburning technology. The FLGR technology requires lower installed capital costs and lower consumption of natural gas to achieve 35 to 45% NOx reductions.
The problem of optimizing and controlling the FLGR system as well as the conventional gas reburning technology or other technologies involving the injection of natural gas and/or other substances is complicated because of (a) the dynamic nature of boiler operation where load changes influence furnace flow velocities, flow patterns, gas temperature, and residence time; (b) the nonlinear interactions of many operating variables; and (c) economic considerations involving the free-market pricing and trading of emission credits or allowances, which make it difficult for boiler operating personnel to interpret impacts and consistently adjust the gas injection to maintain optimal, least-cost, control in real time.
The present invention addresses the aforementioned considerations of and problems encountered in the prior art by providing for the more efficient operation of an electric utility or industrial fossil-fired boiler with injected substances (such as natural gas, ammonia, and urea) above the primary combustion zone, including a reduction in the emission of pollutants, using an artificial neural network approach with multivariable nonlinear constrained optimization algorithms for automatically controlling the injection of the substances.
Accordingly, it is an object of the present invention to reduce emissions of one or more pollutants from a fossil-fired combustion process by optimizing and controlling each of multiple inputs of injected substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and urea) or combination of such or other substances above the primary combustion zone.
It is another object of the present invention to automatically control the injection rate of various inputs above the primary combustion zone to reduce the emission of pollutants, such as NOx and CO, for various process operating conditions.
Yet another object of the present invention is to determine for a fossil-fired combustion process with injected substances above the primary combustion zone, whether it is more cost-effective to achieve additional increments in emission reductions through the injection of additional substance or through the purchase of emission credits in the open market based upon considerations of the optimal operating conditions of the substance injection system, the cost of the incremental injected substance, and the open-market price per ton of emission credits.
A still further object of the present invention is to determine optimal operating conditions for the injected substances using nonlinear constrained optimization methods and artificial neural networks for modeling the nonlinear relationships between the emissions exiting the furnace and the distribution of the injected substances into an upper region of the furnace.
This invention operates to control emissions from fossil-fired boilers through the optimization of the distribution of injected substances above the primary boiler combustion zone. The invention employs artificial neural networks for modeling the nonlinear relationships between the emissions exiting the furnace and the distribution of substances injected into an upper region of the furnace. The mathematical expressions derived from the artificial neural networks are used to solve this multivariable nonlinear constrained optimization problem that provides the optimal substance distribution that minimizes emission levels for a given substance consumption rate. The invention further contemplates an advisory operations support system which determines whether it is more cost-effective to achieve additional increments in emission reductions through the consumption of additional substance (e.g., natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea) or through the direct purchase of emission credits in the open market based upon the optimal operating conditions determined from the aforementioned multivariable optimization, the cost of incremental injected substance, and the open-market price per ton of emission credits.